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    "# Practical 6: Supervised Learning \n",
    "\n",
    "\n",
    "Upon completion of this session you should be able to:\n",
    "- understand how kNN, Naive Bayes, Decision Tree and Random Forest algorithms work.\n",
    "- be able to apply these supervised learning algorithms in Python.\n",
    "\n",
    "---\n",
    "- Materials in this module include resources collected from various open-source online repositories.\n",
    "- Jupyter source file can be downloaded from https://github.com/gaoshangdeakin/SIT384-Jupyter\n",
    "- If you found any issue/bug for this document, please submit an issue at [https://github.com/gaoshangdeakin/SIT384/issues](https://github.com/gaoshangdeakin/SIT384/issues)\n",
    "\n",
    "\n",
    "---\n",
    "\n",
    "\n",
    "\n",
    "This practical session will demonstrate different supervised learning algorithms: kNN, Naive Bayes, Decision Tree and Random Forest.\n",
    "\n",
    "\n",
    "## Background\n",
    "\n",
    "\n",
    "### Part 1 K-NN Classification\n",
    "\n",
    "1.1 [K-NN in Python](#knn)\n",
    "\n",
    "1.2 [Decision Boundary](#db)\n",
    "\n",
    "### Part 2 Naive Bayes Classifier\n",
    "\n",
    "2.1 [NBC by Example](#nbc)\n",
    "\n",
    "2.2 [NBC Exercise](#nbc2)\n",
    "\n",
    "### Part 3 Random Forest\n",
    "\n",
    "3.1 [Decision Trees](#rf2)\n",
    "\n",
    "3.2 [Decision Trees and over-fitting](#rf3)\n",
    "\n",
    "3.3 [Ensembles of Estimators: Random Forests](#rf4)\n",
    "\n",
    "3.4 [Random Forest Regressor](#rf5)\n",
    "\n",
    "3.5 [Random Forest Limitations](#rf6)\n",
    "\n",
    "\n",
    "### Part 4 Confidence Interval\n",
    "\n",
    "4.1 [Population and Sample](#popsample)\n",
    "\n",
    "4.2 [Confidence Interval](#ci)\n",
    "\n",
    "## Tasks\n",
    "\n",
    "## Summary\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "### <span style=\"color:#0b486b\">1. k-Nearest Neighbours Classification</span> \n",
    "\n",
    "kNN is a non-parametric classification technique which is extensively used in practice. Its input consists of the `k` closest training examples and the output is a class membership. An object is classified by a majority vote of its neighbors, with the object being assigned to the class most common among its `k` nearest neighbors (k is a positive integer, typically small). If k = 1, then the object is simply assigned to the class of that single nearest neighbor.\n",
    "\n",
    "**Please note that kNN is different from K-means.** K-means is a clustering algorithm that tries to partition a set of points into K sets (clusters) such that the points in each cluster be close to each other. It is unsupervised because the points have no external classification. kNN is a classification algorithm that in order to determine the classification of a point, combines the class of the k nearest points. It is supervised because you are trying to classify a point based on the known label of other points."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id = \"knn\"></a>\n",
    "\n",
    "### <span style=\"color:#0b486b\">1.1 kNN in Python</span> \n",
    "\n",
    "To be able to illustrate how we perform kNN classification in Python, we need some data first. Therefore we synthesize some data from 3 classes. We assume the data in each class comes from a multivariate random distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "#seaborn: statistical data visualization. \n",
    "#Seaborn is a Python data visualization library based on matplotlib. \n",
    "#It provides a high-level interface for drawing attractive and informative statistical graphics.\n",
    "import seaborn as sns\n",
    "\n",
    "#%matplotlib inline\n",
    "\n",
    "#To switch to seaborn defaults, simply call the set() function.\n",
    "sns.set()"
   ]
  },
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   "metadata": {},
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\n",
      "text/plain": [
       "<Figure size 700x700 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#\n",
    "#Pseudo-random number generators work by performing some operation on a value. \n",
    "#Generally this value is the previous number generated by the generator. \n",
    "#However, the first time you use the generator, there is no previous value.\n",
    "#\n",
    "#Seeding a pseudo-random number generator gives it its first \"previous\" value. \n",
    "#Each seed value will correspond to a sequence of generated values for a given random number generator. \n",
    "#That is, if you provide the same seed twice, you get the same sequence of numbers twice.\n",
    "#\n",
    "#\n",
    "np.random.seed(100)\n",
    "\n",
    "n_per_class = 50\n",
    "colors = ['green', 'blue', 'magenta']\n",
    "\n",
    "mean1 = [-5, 10]\n",
    "cov1 = [[1.5, 0], [0, 1.5]]\n",
    "mean2 = [0, 7]\n",
    "cov2 = [[1.5, 0], [0, 3]]\n",
    "mean3 = [-6, 6]\n",
    "cov3 = [[2, 0], [0, 1.5]]\n",
    "\n",
    "means = [mean1, mean2, mean3]\n",
    "covs = [cov1, cov2, cov3]\n",
    "\n",
    "#\n",
    "#np.random.multivariate_normal()\n",
    "#Draw random samples from a multivariate normal distribution.\n",
    "#\n",
    "#The multivariate normal, multinormal or Gaussian distribution is \n",
    "#a generalization of the one-dimensional normal distribution to higher dimensions. \n",
    "#Such a distribution is specified by its mean and covariance matrix. \n",
    "#These parameters are analogous to the mean (average or “center”) \n",
    "#and variance (standard deviation, or “width,” squared) of the one-dimensional normal distribution.\n",
    "#For detail, go to https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.random.multivariate_normal.html \n",
    "#\n",
    "\n",
    "x11, x12 = np.random.multivariate_normal(means[0], covs[0], n_per_class).T\n",
    "x21, x22 = np.random.multivariate_normal(means[1], covs[1], n_per_class).T\n",
    "x31, x32 = np.random.multivariate_normal(means[2], covs[2], n_per_class).T\n",
    "\n",
    "scale = 75\n",
    "alpha = 0.6\n",
    "\n",
    "fig, ax  = plt.subplots(figsize=(7, 7), dpi=100)\n",
    "ax.scatter(x11, x12, alpha=alpha, color=colors[0], s=scale)\n",
    "ax.scatter(x21, x22, alpha=alpha, color=colors[1], s=scale)\n",
    "ax.scatter(x31, x32, alpha=alpha, color=colors[2], s=scale)\n",
    "\n",
    "ax.set_title(\"synthesized data for 3 classes\")\n",
    "ax.set_xlabel(\"$x_1$\")\n",
    "ax.set_ylabel(\"$x_2$\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then we have to instantiate a kNN classifier from sklearn. Below is how we define K and create kNN classifier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import neighbors\n",
    "\n",
    "weights='uniform'\n",
    "k = 15\n",
    "knn = neighbors.KNeighborsClassifier(k,weights=weights)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now use the above data to create the kNN classifier. We need to pass one array as training features and one array as training labels to the `knn` object. Therefore we have to put all the attributes together (also class labels)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#\n",
    "#np.r_\n",
    "#This is used to concatenate any number of array slices along row (first) axis. \n",
    "#This is a simple way to create numpy arrays quickly and efficiently. \n",
    "#For detail, go to https://docs.scipy.org/doc/numpy/reference/generated/numpy.r_.html\n",
    "#\n",
    "#concatenate all the arrays along row axis  \n",
    "x1 = np.r_[x11, x21, x31]\n",
    "x2 = np.r_[x12, x22, x32]\n",
    "#\n",
    "#np.c_\n",
    "#np.c_ is another way of doing array concatenate.\n",
    "#It translates slice objects to concatenation along the second axis.\n",
    "#e.g. >>> np.c_[np.array([[1,2,3]]), 0, 0, np.array([[4,5,6]])]\n",
    "#array([[1, 2, 3, 0, 0, 4, 5, 6]])\n",
    "#\n",
    "##concatenate all the arrays along column axis  \n",
    "X_train = np.c_[x1, x2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#general Y_train label output for the X_train input: 50 zero (class 0), 50 one (class 1) and 50 two (class 2)\n",
    "Y_train = np.r_[0*np.ones(n_per_class), 1*np.ones(n_per_class), 2*np.ones(n_per_class)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can fit the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "                     metric_params=None, n_jobs=None, n_neighbors=15, p=2,\n",
       "                     weights='uniform')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn.fit(X_train, Y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we will see how kNN classifies a point."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "                     metric_params=None, n_jobs=None, n_neighbors=1, p=2,\n",
       "                     weights='uniform')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#if set k=1, only one nearest neighbor\n",
    "k = 1\n",
    "knn = neighbors.KNeighborsClassifier(k)\n",
    "knn.fit(X_train, Y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib.colors import ListedColormap\n",
    "cmap_bold = ListedColormap(['green', 'blue', 'magenta'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '3-Class classification (k = 5)\\n Red point is predicted as class green')"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(figsize=(7, 7))\n",
    "\n",
    "#plot the classification of X_train\n",
    "ax.scatter(X_train[:, 0], X_train[:, 1], c=Y_train, cmap=cmap_bold, alpha=alpha, s=scale)\n",
    "\n",
    "plt.title(\"3-Class classification (k = {})\".format(k))\n",
    "\n",
    "#create an input to predict its label\n",
    "X_test = [[-7, 10]]\n",
    "Y_pred = knn.predict(X_test)\n",
    "\n",
    "#to check the predicted label for the X_test\n",
    "print(Y_pred)\n",
    "\n",
    "#plot the test input\n",
    "ax.scatter(X_test[0][0], X_test[0][1], marker=\"x\", s=scale, lw=2, c='k')\n",
    "#as you can see, the test input is displayed in color 'k'\n",
    "#how could it be colored based on the prediction Y_pred?\n",
    "\n",
    "ax.set_title(\"3-Class classification (k = {})\\n Red point is predicted as class {}\".format(k, colors[Y_pred.astype(int)[0]]))\n",
    "\n",
    "#plot the test input using the predicted color\n",
    "#ax.scatter(X_test[0][0], X_test[0][1], marker=\"x\", s=scale, lw=2, c=colors[Y_pred.astype(int)[0]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id = \"db\"></a>\n",
    "\n",
    "### <span style=\"color:#0b486b\">1.2 Decision Boundry</span> "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "kNN effectively partitions the feature space into different sets and assigns the same class label to points belonging to the same partition. This partitioning changes as we change k. We illustrate this below. As you see bigger values of k, partition the space more smoothly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib.colors import ListedColormap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '3-Class classification (k = 15)')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "k = 15\n",
    "knn = neighbors.KNeighborsClassifier(k, weights=weights)\n",
    "knn.fit(X_train, Y_train)\n",
    "\n",
    "# step size in the mesh\n",
    "h = 0.05\n",
    "\n",
    "# Create colour maps\n",
    "cmap_light = ListedColormap(['#AAFFAA', '#AAAAFF', '#FFAAAA'])\n",
    "cmap_bold = ListedColormap(['green', 'blue', 'magenta'])\n",
    "\n",
    "x1_min, x1_max = X_train[:, 0].min() - 1, X_train[:, 0].max() + 1\n",
    "x2_min, x2_max = X_train[:, 1].min() - 1, X_train[:, 1].max() + 1\n",
    "xx1, xx2 = np.meshgrid(np.arange(x1_min, x1_max, h), np.arange(x2_min, x2_max, h))\n",
    "\n",
    "Z = knn.predict(np.c_[xx1.ravel(), xx2.ravel()])\n",
    "\n",
    "# Put the result into a color plot\n",
    "Z = Z.reshape(xx1.shape)\n",
    "\n",
    "fig,ax = plt.subplots(figsize=(7, 7))\n",
    "ax.pcolormesh(xx1, xx2, Z, cmap=cmap_light)\n",
    "\n",
    "# Plot also the training points\n",
    "ax.scatter(X_train[:, 0], X_train[:, 1], c=Y_train, cmap=cmap_bold, alpha=alpha, s=scale)\n",
    "\n",
    "plt.xlim(xx1.min(), xx1.max())\n",
    "plt.ylim(xx2.min(), xx2.max())\n",
    "plt.title(\"3-Class classification (k = {})\".format(k))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we will investigate the effect of `'k'` on decision boundaries. Lets train a classifier with `k=1` which means we only use the label of the closest point to predict the label of a test point."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '3-Class classification (k = 1)')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "k = 1\n",
    "knn = neighbors.KNeighborsClassifier(k, weights=weights)\n",
    "knn.fit(X_train, Y_train)\n",
    "\n",
    "Z = knn.predict(np.c_[xx1.ravel(), xx2.ravel()])\n",
    "Z = Z.reshape(xx1.shape)\n",
    "\n",
    "fig,ax = plt.subplots(figsize=(7, 7))\n",
    "ax.pcolormesh(xx1, xx2, Z, cmap=cmap_light)\n",
    "\n",
    "ax.scatter(X_train[:, 0], X_train[:, 1], c=Y_train, cmap=cmap_bold, alpha=alpha, s=scale)\n",
    "\n",
    "plt.xlim(xx1.min(), xx1.max())\n",
    "plt.ylim(xx2.min(), xx2.max())\n",
    "plt.title(\"3-Class classification (k = {})\".format(k))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '3-Class classification (k = 2)')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "k = 2\n",
    "knn = neighbors.KNeighborsClassifier(k, weights=weights)\n",
    "knn.fit(X_train, Y_train)\n",
    "\n",
    "Z = knn.predict(np.c_[xx1.ravel(), xx2.ravel()])\n",
    "Z = Z.reshape(xx1.shape)\n",
    "\n",
    "fig,ax = plt.subplots(figsize=(7, 7))\n",
    "ax.pcolormesh(xx1, xx2, Z, cmap=cmap_light)\n",
    "\n",
    "ax.scatter(X_train[:, 0], X_train[:, 1], c=Y_train, cmap=cmap_bold, alpha=alpha, s=scale)\n",
    "\n",
    "plt.xlim(xx1.min(), xx1.max())\n",
    "plt.ylim(xx2.min(), xx2.max())\n",
    "plt.title(\"3-Class classification (k = {})\".format(k))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '3-Class classification (k = 3)')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "k = 3\n",
    "knn = neighbors.KNeighborsClassifier(k, weights=weights)\n",
    "knn.fit(X_train, Y_train)\n",
    "\n",
    "Z = knn.predict(np.c_[xx1.ravel(), xx2.ravel()])\n",
    "Z = Z.reshape(xx1.shape)\n",
    "\n",
    "fig,ax = plt.subplots(figsize=(7, 7))\n",
    "ax.pcolormesh(xx1, xx2, Z, cmap=cmap_light)\n",
    "\n",
    "ax.scatter(X_train[:, 0], X_train[:, 1], c=Y_train, cmap=cmap_bold, alpha=alpha, s=scale)\n",
    "\n",
    "plt.xlim(xx1.min(), xx1.max())\n",
    "plt.ylim(xx2.min(), xx2.max())\n",
    "plt.title(\"3-Class classification (k = {})\".format(k))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '3-Class classification (k = 5)')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "k = 5\n",
    "knn = neighbors.KNeighborsClassifier(k, weights=weights)\n",
    "knn.fit(X_train, Y_train)\n",
    "\n",
    "Z = knn.predict(np.c_[xx1.ravel(), xx2.ravel()])\n",
    "Z = Z.reshape(xx1.shape)\n",
    "\n",
    "fig,ax = plt.subplots(figsize=(7, 7))\n",
    "ax.pcolormesh(xx1, xx2, Z, cmap=cmap_light)\n",
    "\n",
    "ax.scatter(X_train[:, 0], X_train[:, 1], c=Y_train, cmap=cmap_bold, alpha=alpha, s=scale)\n",
    "\n",
    "plt.xlim(xx1.min(), xx1.max())\n",
    "plt.ylim(xx2.min(), xx2.max())\n",
    "plt.title(\"3-Class classification (k = {})\".format(k))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.2.1 Prediction\n",
    "\n",
    "Play with the `X_test` and `k` to see how the classifier behaves."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '3-Class classification (k = 5)\\n Red point is predicted as class green')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "k = 5\n",
    "knn = neighbors.KNeighborsClassifier(k, weights=weights)\n",
    "knn.fit(X_train, Y_train)\n",
    "\n",
    "Z = knn.predict(np.c_[xx1.ravel(), xx2.ravel()])\n",
    "Z = Z.reshape(xx1.shape)\n",
    "\n",
    "fig,ax = plt.subplots(figsize=(7, 7))\n",
    "ax.pcolormesh(xx1, xx2, Z, cmap=cmap_light)\n",
    "\n",
    "ax.scatter(X_train[:, 0], X_train[:, 1], c=Y_train, cmap=cmap_bold, alpha=alpha, s=scale)\n",
    "\n",
    "plt.xlim(xx1.min(), xx1.max())\n",
    "plt.ylim(xx2.min(), xx2.max())\n",
    "plt.title(\"3-Class classification (k = {})\".format(k))\n",
    "\n",
    "X_test = [[-4, 8]]\n",
    "Y_pred = knn.predict(X_test)\n",
    "ax.scatter(X_test[0][0], X_test[0][1], alpha=0.95, color='r', s=3*scale)\n",
    "\n",
    "ax.set_title(\"3-Class classification (k = {})\\n Red point is predicted as class {}\".format(k, colors[Y_pred.astype(int)[0]]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now instead of predicting the class label for one point, we use our model to predict the labels of multiple points.\n",
    "\n",
    "First we generate some test data from the first class. This way we know the true class labels. Then we can use the `kNN` classifier to predict labels for the test data and get the predicted class labels. A measure of  accuracy for the classifier can be defined by comparing the true and predicted labels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_test = 100\n",
    "X1_test, X2_test = np.random.multivariate_normal(mean1, cov1, n_test).T\n",
    "Y_true = 0 * np.ones(n_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_test = np.c_[X1_test, X2_test]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "Y_pred = knn.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       2., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 2., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Y_pred"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How many times the classifier predicts the labels correctly?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True, False,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True, False,\n",
       "        True, False,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True, False,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Y_pred == Y_true"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " Accuracy:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.96"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(sum(Y_pred == Y_true) + 0.0) / n_test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise**: Repeat the previous experiment with a classifier which has been trained with a different `k`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <span style=\"color:#0b486b\">2. Naive Bayes Classifier</span> \n",
    "\n",
    "\n",
    "Naive Bayes is one of the most practical classification machine learning algorithms. It is  based on Bayes’ Theorem with an assumption of independence among predictors. It is: \n",
    "\n",
    "* fast\n",
    "* good performance\n",
    "* simple yet very effective\n",
    "* robust to irrelative features\n",
    "\n",
    "So why is it called naive?\n",
    "\n",
    "Because it does not consider the dependency between features and assume all features are independent of each other which is not the case in reality. This is a naive assumption, hence the name.\n",
    "\n",
    "Naive Bayes model is easy to build and particularly useful for very large data sets. Along with simplicity, Naive Bayes is known to outperform even highly sophisticated classification methods. There are many interesting tutorials explaining the Bayes' Theorem for beginners via google, eg. [https://dzone.com/articles/naive-bayes-tutorial-naive-bayes-classifier-in-pyt](https://dzone.com/articles/naive-bayes-tutorial-naive-bayes-classifier-in-pyt). \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The accuracy is very good although with this naive assumption. A famous example of NB usage is spam filtering."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id = \"nbc\"></a>\n",
    "### <span style=\"color:#0b486b\">2.1 NBC by Example</span> \n",
    "\n",
    "We assume we have collected the below data over the past 5 days. Based on this data, can we predict if our subject will play in a setting like:\n",
    "\n",
    "    outlook  = overcast\n",
    "    temp     = hot\n",
    "    humidity = normal\n",
    "    windy    = no"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!-- <img src=\"nb_data.png\" width=\"800\"> -->\n",
    "<img src=\"./images/p06/nb_data.png\" width=\"800\">\n",
    "<br />"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we have to find a representation for our data. We can construct a dictionary to convert stings into numbers and then save them in a dataframe. \n",
    "\n",
    "    outlook: sunny=0, overcast=1, rainy=2\n",
    "    temp: hot=0, mild=1, cool=2\n",
    "    humidity: normal=0, high=1\n",
    "    wind: no=0, yes=1\n",
    "    play: no=0, yes=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "from __future__ import division\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = {\n",
    "    'outlook': [0, 1, 2, 0, 1],\n",
    "    'temp'   : [0, 1, 2, 1, 0],\n",
    "    'humid'  : [0, 0, 1, 0, 1],\n",
    "    'wind'   : [0, 0, 1, 1, 0],\n",
    "    'play'   : [1, 1, 0, 0, 0,]    \n",
    "}\n",
    "\n",
    "df = pd.DataFrame(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we use Bayes rule to construct a Naive Bayes classifier. We can write:\n",
    "\n",
    "$$Pr\\left(p|o,t,h,w\\right)\\propto Pr\\left(p\\right)Pr(o|p)Pr(t|p)Pr(h|p)Pr(w|p)$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To calculate $Pr(p)$ we use marginal probablity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def marginal_prob(df, col):\n",
    "    ll = [(ss, (df[col] == ss).sum()) for ss in set(df[col])]\n",
    "    total_count = [b for a,b in ll]\n",
    "    total_count = sum(total_count)\n",
    "    \n",
    "    ll2 = [(a, b/total_count) for a, b in ll]\n",
    "    return dict(ll2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To calculate probability of a feature given the class (play) we use conditinoal probability."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "def conditional_prob(df, f, c, val):\n",
    "    df2 = df[df[c] == val][f]\n",
    "    ll = [[ss, (df2 == ss).sum()] for ss in set(df2)]\n",
    "    total_count = [b for a,b in ll]\n",
    "    total_count = sum(total_count)\n",
    "    \n",
    "    ll2 = [(a, b/total_count) for a, b in ll]\n",
    "    return dict(ll2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can use Bayes rule:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "probability of not playing: 0.06896551724137928\n",
      "probability of playing    : 0.9310344827586208\n"
     ]
    }
   ],
   "source": [
    "#outlook: sunny=0, overcast=1, rainy=2\n",
    "#temp: hot=0, mild=1, cool=2\n",
    "#humidity: normal=0, high=1\n",
    "#wind: no=0, yes=1\n",
    "#play: no=0, yes=1\n",
    "\n",
    "#Given:     \n",
    "#outlook  = overcast\n",
    "#temp     = hot\n",
    "#humidity = normal\n",
    "#windy    = no\n",
    "\n",
    "o = 1\n",
    "t = 0\n",
    "h = 0\n",
    "w = 0\n",
    "\n",
    "c = 0\n",
    "p0 = marginal_prob(df, 'play')[c] * conditional_prob(df, 'outlook', 'play', c)[o] * conditional_prob(df, 'temp', 'play', c)[t] \\\n",
    "* conditional_prob(df, 'humid', 'play', c)[h] * conditional_prob(df, 'wind', 'play', c)[w]\n",
    "\n",
    "c = 1\n",
    "p1 = marginal_prob(df, 'play')[c] * conditional_prob(df, 'outlook', 'play', c)[o] * conditional_prob(df, 'temp', 'play', c)[t] \\\n",
    "* conditional_prob(df, 'humid', 'play', c)[h] * conditional_prob(df, 'wind', 'play', c)[w]\n",
    "\n",
    "# normalizing\n",
    "p_sum = p0 + p1\n",
    "p0 /= p_sum\n",
    "p1 /= p_sum\n",
    "\n",
    "print (\"probability of not playing: {}\".format(p0))\n",
    "print (\"probability of playing    : {}\".format(p1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id = \"rf1\"></a>\n",
    "\n",
    "## 3. Random Forest\n",
    "\n",
    "Random forests are an example of an *ensemble learner* built on decision trees.\n",
    "For this reason we'll start by discussing decision trees themselves.\n",
    "\n",
    "Decision trees are extremely intuitive ways to classifying or labeling objects: you simply ask a series of questions designed to zero-in on the classification."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn; \n",
    "from sklearn.linear_model import LinearRegression\n",
    "from scipy import stats\n",
    "import pylab as pl\n",
    "\n",
    "seaborn.set()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Download [fig_code.zip](fig_code.zip) from week6 folder on Clouddeakin or [https://github.com/gaoshangdeakin/SIT384-libs/](https://github.com/gaoshangdeakin/SIT384-libs/). Extract and save the fig_code folder in the same folder where your script is."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import fig_code\n",
    "fig_code.plot_example_decision_tree()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The binary splitting makes this extremely efficient.\n",
    "As always, though, the trick is to *ask the right questions*.\n",
    "This is where the algorithmic process comes in: in training a decision tree classifier, the algorithm looks at the features and decides which questions (or \"splits\") contain the most information.\n",
    "\n",
    "<a id = \"rf2\"></a>\n",
    "\n",
    "### 3.1 Creating a Decision Tree\n",
    "\n",
    "Here's an example of a decision tree classifier in scikit-learn. We'll start by defining some two-dimensional labeled data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.datasets import make_blobs\n",
    "\n",
    "X, y = make_blobs(n_samples=300, centers=4,\n",
    "                  random_state=0, cluster_std=1.0)\n",
    "plt.scatter(X[:, 0], X[:, 1], c=y, s=50, cmap='rainbow');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7ea9786cd1064522a2c431034a8a16ae",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='depth', options=(1, 5), value=1), Output()), _dom_classes=('widget…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# We have some convenience functions in the repository that help \n",
    "from fig_code import visualize_tree, plot_tree_interactive\n",
    "#from IPython.html.widgets import interact\n",
    "\n",
    "# Now using IPython's ``interact`` (available in IPython 2.0+, and requires a live kernel) we can view the decision tree splits:\n",
    "plot_tree_interactive(X, y);\n",
    "\n",
    "#interact(fit_randomized_tree, random_state=[0, 100]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that at each increase in depth, every node is split in two **except** those nodes which contain only a single class.\n",
    "The result is a very fast **non-parametric** classification, and can be extremely useful in practice.\n",
    "\n",
    "**Question: Do you see any problems with this?**\n",
    "\n",
    "<a id = \"rf3\"></a>\n",
    "\n",
    "### 3.2 Decision Trees and over-fitting\n",
    "\n",
    "One issue with decision trees is that it is very easy to create trees which **over-fit** the data. That is, they are flexible enough that they can learn the structure of the noise in the data rather than the signal! For example, take a look at two trees built on two subsets of this dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "clf = DecisionTreeClassifier()\n",
    "\n",
    "plt.figure()\n",
    "visualize_tree(clf, X[:200], y[:200], boundaries=False)\n",
    "plt.figure()\n",
    "visualize_tree(clf, X[-200:], y[-200:], boundaries=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The details of the classifications are completely different! That is an indication of **over-fitting**: when you predict the value for a new point, the result is more reflective of the noise in the model rather than the signal.\n",
    "\n",
    "<a id = \"rf4\"></a>\n",
    "\n",
    "### 3.3 Ensembles of Estimators: Random Forests\n",
    "\n",
    "One possible way to address over-fitting is to use an **Ensemble Method**: this is a meta-estimator which essentially averages the results of many individual estimators which over-fit the data. Somewhat surprisingly, the resulting estimates are much more robust and accurate than the individual estimates which make them up!\n",
    "\n",
    "One of the most common ensemble methods is the **Random Forest**, in which the ensemble is made up of many decision trees which are in some way perturbed.\n",
    "\n",
    "There are volumes of theory and precedent about how to randomize these trees, but as an example, let's imagine an ensemble of estimators fit on subsets of the data. We can get an idea of what these might look like as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0f2cd604169c43e6aa82c2d8f708a417",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='random_state', options=(0, 100), value=0), Output()), _dom_classes…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def fit_randomized_tree(random_state=0):\n",
    "    X, y = make_blobs(n_samples=300, centers=4,\n",
    "                      random_state=0, cluster_std=2.0)\n",
    "    clf = DecisionTreeClassifier(max_depth=15)\n",
    "    \n",
    "    rng = np.random.RandomState(random_state)\n",
    "    i = np.arange(len(y))\n",
    "    rng.shuffle(i)\n",
    "    visualize_tree(clf, X[i[:250]], y[i[:250]], boundaries=False,\n",
    "                   xlim=(X[:, 0].min(), X[:, 0].max()),\n",
    "                   ylim=(X[:, 1].min(), X[:, 1].max()))\n",
    "    \n",
    "from IPython.html.widgets import interact\n",
    "interact(fit_randomized_tree, random_state=[0, 100]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "See how the details of the model change as a function of the sample, while the larger characteristics remain the same!\n",
    "The random forest classifier will do something similar to this, but use a combined version of all these trees to arrive at a final answer:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "clf = RandomForestClassifier(n_estimators=100, random_state=0, n_jobs=-1)\n",
    "visualize_tree(clf, X, y, boundaries=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By averaging over 100 randomly perturbed models, we end up with an overall model which is a much better fit to our data!\n",
    "\n",
    "*(Note: above we randomized the model through sub-sampling... Random Forests use more sophisticated means of randomization, which you can read about in, e.g. the [scikit-learn documentation](http://scikit-learn.org/stable/modules/ensemble.html#forest)*)\n",
    "\n",
    "<a id = \"rf5\"></a>\n",
    "\n",
    "### 3.4 Random Forest Regressor\n",
    "\n",
    "Above we were considering random forests within the context of classification.\n",
    "Random forests can also be made to work in the case of regression (that is, continuous rather than categorical variables). The estimator to use for this is ``sklearn.ensemble.RandomForestRegressor``.\n",
    "\n",
    "Let's quickly demonstrate how this can be used:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "x = 10 * np.random.rand(100)\n",
    "\n",
    "def model(x, sigma=0.3):\n",
    "    fast_oscillation = np.sin(5 * x)\n",
    "    slow_oscillation = np.sin(0.5 * x)\n",
    "    noise = sigma * np.random.randn(len(x))\n",
    "\n",
    "    return slow_oscillation + fast_oscillation + noise\n",
    "\n",
    "y = model(x)\n",
    "plt.errorbar(x, y, 0.3, fmt='o');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xfit = np.linspace(0, 10, 1000)\n",
    "yfit = RandomForestRegressor(100).fit(x[:, None], y).predict(xfit[:, None])\n",
    "ytrue = model(xfit, 0)\n",
    "\n",
    "plt.errorbar(x, y, 0.3, fmt='o')\n",
    "plt.plot(xfit, yfit, '-r');\n",
    "plt.plot(xfit, ytrue, '-k', alpha=0.5);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, the non-parametric random forest model is flexible enough to fit the multi-period data, without us even specifying a multi-period model!\n",
    "\n",
    "Tradeoff between simplicity and thinking about what your data is.\n",
    "\n",
    "Feature engineering is important, need to know your domain: Fourier transform frequency distribution.\n",
    "\n",
    "<a id = \"rf6\"></a>\n",
    "\n",
    "### 3.5 Random Forest Limitations\n",
    "\n",
    "The following data scenarios are not well suited for random forests:\n",
    "* y: lots of 0, few 1\n",
    "* Structured data like images where a neural network might be better\n",
    "* Small data size which might lead to overfitting\n",
    "* High dimensional data where a linear model might work better"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## <span style=\"color:#0b486b\">4. Confidence Interval</span> "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id = \"popsample\"></a>\n",
    "\n",
    "### <span style=\"color:#0b486b\">4.1 Population vs Sample</span> \n",
    "\n",
    "The main difference between population and sample comes down to how observations are assigned to dataset. A **population** includes all of the elements from the dataset. A **sample** consists of one or more observations from the population. In other words **population** is the entire collection of the desired measurable characteristic that we would have, if we could collect it. \n",
    "\n",
    "For example if suppose we want to find the average height of 2nd grade students in Australia. The population would be all the students who are studying in 2nd grade in Australia. But most likely we can not measure the height of all Australian 2nd grade students. It is not feasible. So what do we do? **We sample!**. We collect the height of some of Australian 2nd graders and based on that, we **estimate** the average height of the population (all of Australian 2nd grade students). The sample could be 2nd grade students in one class of one school, or multiple classes of multiple schools in one state, or  multiple schools in multiple states, or etc.\n",
    "\n",
    "A measurable statistic of a population (such as mean) is called a **parameter**. But a measurable characteristic of a sample is called **statistic**.\n",
    "\n",
    "----\n",
    "<a id = \"ci\"></a> \n",
    "\n",
    "### <span style=\"color:#0b486b\">4.2 Confidence Interval</span> \n",
    "\n",
    "As stated in previous section, population parameter is unknown. Confidence interval is a type of interval estimate of a population parameter calculated from sample statistics. It is an interval estimate combined with a probability.\n",
    "\n",
    "For the aforementioned example, it means that without collecting the height of all Aussie 2nd graders, we can estimate the average height by collecting a sample and using the below formula:\n",
    "\n",
    "\n",
    "$$Confidence\\, Interval=\\bar{X}\\pm z\\frac{s}{\\sqrt{n}}$$\n",
    "\n",
    "$s$ is the sample standard deviation, $n$ is the sample size, and $z$ is often read from a table.\n",
    "\n",
    "    confidence level (%)     z\n",
    "         \n",
    "            70              1.04 \n",
    "            75              1.15\n",
    "            80              1.28 \n",
    "            85              1.44 \n",
    "            90              1.645\n",
    "            92              1.75\n",
    "            95              1.96\n",
    "            96              2.05\n",
    "            98              2.33\n",
    "            99              2.58"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now lets use an example to clarify this concept."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.stats as ss\n",
    "import seaborn as sns\n",
    "\n",
    "%matplotlib inline\n",
    "sns.set()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we create a population. Please note that we do not use the population in our computation. We use samples from it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "mu, sigma = 10, 2\n",
    "n_population = 10000\n",
    "population = np.random.normal(mu, sigma, n_population)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'population histogram, $\\\\mu=10$, $\\\\sigma=2$ ')"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.hist(population, bins=25)\n",
    "ax.set_title(r\"population histogram, $\\mu={}$, $\\sigma={}$ \".format(mu, sigma))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we sample multiple times from this population."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_trials = 1000\n",
    "sample_size = 500\n",
    "samples = np.zeros([n_trials, sample_size])\n",
    "sample_std = np.zeros(n_trials)\n",
    "sample_mean = np.zeros(n_trials)\n",
    "\n",
    "for i in range(n_trials):\n",
    "    samples[i] = np.random.choice(population, size=sample_size, replace=False)\n",
    "    sample_mean[i] = samples[i].mean()\n",
    "    sample_std[i] = samples[i].std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x250a0020288>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "i = 200\n",
    "se = sample_std[i] / np.sqrt(sample_size)\n",
    "dist = ss.distributions.norm(sample_mean[i], se)\n",
    "z = 1.96\n",
    "\n",
    "x = np.linspace(9.5, 10.5, 100)\n",
    "y = dist.pdf(x)\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "    \n",
    "ax.hist(sample_mean, density=True, bins=20, label='sample means')\n",
    "ax.plot(x, y, label=\"$N(\\mu_{i},se)$\")\n",
    "ax.vlines(sample_mean[i] + z*se, 0, 5, label='$\\mu_i \\pm z\\sigma_i$')\n",
    "ax.vlines(sample_mean[i] - z*se, 0, 5)\n",
    "\n",
    "ax.set_title(\"distribution of sample statistics\\ni={}\".format(i))\n",
    "ax.legend()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <span style=\"color:#0b486b\">Tasks</span>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Try the provided examples and get yourself familiar with sample code before attempting portolio tasks.\n",
    "\n",
    "Please show your attempt to your tutor before you leave the lab, or email your files to your coordinator if you are an off-campus student."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <span style=\"color:#0b486b\">Summary</span>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this session we have covered: \n",
    " - different supervised learning algorithms.\n",
    " - how to apply the supervised learning algorithms in Python."
   ]
  }
 ],
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